A3 Refereed book chapter or chapter in a compilation book
Modelling of Postglacial Landscape Development
Authors: Pohjola J, Turunen J, Lipping T, Sivula A, Marila M
Editors: Jari Pohjola, Jari Turunen, Tarmo Lipping, Anna Sivula, Marko Marila
Publisher: SPRINGER INTERNATIONAL PUBLISHING AG, GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
Publication year: 2019
Book title : Historical Perspectives to Postglacial Uplift: Case Studies from the Lower Satakunta Region
Journal acronym: SPRINGERBRIEF GEOGR
Series title: SpringerBriefs in Geography
First page : 37
Last page: 48
Number of pages: 12
ISBN: 978-3-030-00970-0
ISSN: 2211-4165
DOI: https://doi.org/10.1007/978-3-030-00970-0_3
Abstract
The postglacial land uplift process has been modelled using two different approaches: by modelling the geodynamics of the earth's crust (also referred to as Glacial Isostatic Adjustment (GIA) modelling) or by fitting mathematical models to existing archaeological and geological data (referred to as semi-empirical modelling). Although the semi-empirical models are not based on the physical properties of the earth's crust, they are easy to implement and can adapt better to local variations when compared to the GIA models. Semi-empirical models are fitted to the ice retreat data, eustatic sea level dynamics and lake isolation data on past shoreline displacement. As most of these data sources involve uncertainties, the land uplift process can be modelled probabilistically using the Monte Carlo method.
The postglacial land uplift process has been modelled using two different approaches: by modelling the geodynamics of the earth's crust (also referred to as Glacial Isostatic Adjustment (GIA) modelling) or by fitting mathematical models to existing archaeological and geological data (referred to as semi-empirical modelling). Although the semi-empirical models are not based on the physical properties of the earth's crust, they are easy to implement and can adapt better to local variations when compared to the GIA models. Semi-empirical models are fitted to the ice retreat data, eustatic sea level dynamics and lake isolation data on past shoreline displacement. As most of these data sources involve uncertainties, the land uplift process can be modelled probabilistically using the Monte Carlo method.
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